When an enterprise undertakes an Augmented Analytics project, it is typically doing so because it wishes to initiate data democratization, improve data literacy among its team members and create Citizen Data Scientists. The organization looks for a solution that is easy enough for its business users and intuitive enough to produce clear results; one that also provides sophisticated functionality and features and will produce a suitable Return on Investment (ROI) and Total Cost of Ownership (TCO).
What many businesses fail to comprehend is that the right Augmented Analytics solution will also provide significant benefits and advantages to Data Scientists and business analysts.
Did you know that industry analysts predict the augmented analytics market will reach $30 billion USD within the next three years? There are many reasons for this growing popularity. One of those reasons is the ability to leverage this solution across the entire enterprise (not just for business users, but for IT professionals, business analysts and data scientists as well).
While Data Scientists can utilize many sophisticated tools and techniques to gather and analyze data, the process is often manual, time-consuming and complex. While these more advanced processes and tools are appropriate for strategic outcomes and refined results, there are often times when a Data Scientist can make use of Augmented Analytics to gather and analyze data and, where appropriate, to collaborate with business users, managers and executives. For example, a Data Scientist can use PMML integration to Import models created in other languages like R and Python with a PMML format, and use those models with analytical workflows to roll out predictive models to users, enabling business users to participate in analysis and making Data Scientists more productive.
In today’s enterprise, Data Scientists typically spend up to 40% of their time preparing and enriching data. That is time that could be spent on more strategic goals. A Data Scientist role within the organization is meant to support data analytics that require 100% accuracy, and to focus on strategy as a statistical expert.
Let’s consider some of the benefits and advantages inherent in Data Scientist use of Augmented Analytics solutions.
AUGMENTED ANALYTICS SUPPLEMENTS DATA SCIENTIST TOOLS AND TECHNIQUES
- Quickly create datasets using Self-Serve Data Preparation, without the use of SQL or ETL
- Prepare data for analysis quickly, allowing the Data Scientist to use their time more strategically
- Use Smart Visualization tools to manage the output of algorithms in R, Python or other platforms
- Roll out interactive Predictive Models in a production environment to provide access to business users
- Leverage PMML integration to quickly import models from varied platforms and use within analytics workflow
When the organization provides its business users with access to Augmented Analytics, Data Scientists can optimize their time and resources.
AUGMENTED ANALYTICS FOR BUSINESS USERS CAN AND WILL SUPPORT DATA SCIENTISTS
- Fewer day-to-day requests and interruptions
- Ability to focus on crucial, strategic projects
- Involvement in projects where 100% accuracy is required
- Focus on mature modeling requirements
In short, when an enterprise provides access to Augmented Analytics to both its business users and its Data Scientists, it ensures that the investment in existing systems and tools will be better leveraged, and that the new tools and solutions will provide significant ROI. It also optimizes its resources, knowledge and time.
As we have outlined in this article, it is important to recognize the value of Augmented Analytics both for your team members and for your Data Scientists and Business Analysts. Make the most of your investment in an analytics solution by allowing ALL members of your organization to use these tools in a way that is meaningful to them. Do not place limitations on your success! Contact Us to find out how we can help you plan and achieve your goals.
Original Post : Your Data Scientists Can Use Augmented Analytics Too!
